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Shopping Malls Accessibility Evaluation Based on Microscopic Traffic Flow Simulation

  • Mihails SavrasovsEmail author
  • Irina Pticina
  • Valery Zemlynikin
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 879)

Abstract

The task of shopping mall accessibility evaluation is a vivid problem from a business perspective and in the same time from the public sector and urban development. Business entities are interested to have higher accessibility level to increase the profit in the same time the public sector is interested in sustainable development of the urban areas. Current paper presents the approach to evaluate accessibility of the shopping malls by the visitors based on microscopic traffic flow simulation. The proposed approach in based on idea, that the “last mile” challenge in logistics is also actual in case of the shopping malls. The main factors influencing “last mile” in this case are: usually location of the shopping malls is planned to have maximum of passing flows, it means that a network around shopping mall could be congested much and it is quit problematic to get into shopping mall; usually the number of parking lots are limited and in case of shopping mall popularity visitors are spending significant amount of time to find the free lots; also, a very important issue is related with leaving the shopping mall parking area, as it could be the situation that it is easier to get in when to get out from parking. To evaluate the influence of the mentioned above factors to the accessibility it is proposed to utilize microscopic traffic flow simulation. The paper formulates the methodology for evaluation of accessibility of the shopping malls and demonstrates its applicability based on case study.

Keywords

Shopping mall Accessibility Traffic simulation Last mile 

Notes

Acknowledgements

This work has been supported by the ALLIANCE project (http://alliance-project.eu/) and has been funded within the European Commission’s H2020 Programme under contract number 692426. This paper expresses the opinions of the authors and not necessarily those of the European Commission. The European Commission is not liable for any use that may be made of the information contained in this paper.

References

  1. 1.
    ICSC: Shopping Center Definitions. https://www.icsc.org/news-and-views/research/shopping-center-definitions. Accessed 30 Jan 2018
  2. 2.
    Mohamad, M.Y., Katheeri, F.A., Salam, A.: A GIS application for location selection and customers’ preferences for shopping malls in Al Ain City; UAE. Am. J. Geogr. Inf. Syst. 4(2), 76–86 (2015)Google Scholar
  3. 3.
    Ahmed, A., Muhammad, N., Mohammed, M.U., Idris, Y.: GIS-based analysis police stations distributions in Kano Metropolis. IOSR J. Comput. Eng. 8(4), 72–78 (2013)CrossRefGoogle Scholar
  4. 4.
    Pashkevich, A., Puławska, S.: Assessment of shopping malls accessibility: case study of Krakow. En XII Congreso de ingeniería del transporte. 7, 8 y 9 de Junio, Valencia (España). Editorial Universitat Politècnica de València, pp. 1743–1758 (2016)Google Scholar
  5. 5.
    Litman, T.: Well Measured. Developing Indicators for Sustainable and Livable Transport Planning. Victoria Transport Policy Institute (2015)Google Scholar
  6. 6.
    Geurs, K.T., van Ritsema Eck, J.R.: Accessibility measures: review and applications. RIVM report 408505 006, National Institute of Public Health and Environment, Bilthoven (2001)Google Scholar
  7. 7.
    Scheurer, J., Curtis, C.: Accessibility Measures: Overview and Practical Applications, Department of Urban and Regional Planning, Curtin University, Perth, p. 52 (2007)Google Scholar
  8. 8.
    Bhat, C., Handy, S., Kockelman, K., Mahmassani, H., Chen, Q., Weston, L.: Development of an Urban Accessibility Index: Literature Review. Research project conducted for the Texas Department of Transportation. Center for Transportation Research, University of Texas, Austin (TX), USA (2000)Google Scholar
  9. 9.
    Porta, S., Crucitti, P., Latora, V.: The network analysis of urban streets: a primal approach. Environ. Plan. B Plan. Des. 33(5), 705–725 (2006)Google Scholar
  10. 10.
    Porta, S., Crucitti, P., Latora, V.: The network analysis of urban streets: a dual approach. Phys. A, Stat. Mech. Appl. 369(2), 853–866 (2006)Google Scholar
  11. 11.
    Ding, Y., Lu, H., Sun, X.: Impact of improved accessibility on shopping activity: person-based measure. J. Urban Plan. Dev. 142(3), 04016006 (2016)Google Scholar
  12. 12.
    Guy, C.M.: The assessment of access to local shopping opportunities: a comparison of accessibility measures. Environ. Plan. B 10, 219–238 (1983)CrossRefGoogle Scholar
  13. 13.
    Van Meter, E., Lawson, A.B., Colabianchi, N., Nichols, M., Hibbert, J., Porter, D., Liese, A.D.: Spatial accessibility and availability measures and statistical properties in the food environment. Spat. Spatiotemporal Epidemiol. 2, 35–47 (2011)Google Scholar
  14. 14.
    Widener, M.J.: Comparing measures of accessibility to urban supermarkets for transit and auto users. Prof. Geogr. 69(3), 1–10 (2016)Google Scholar
  15. 15.
    Farbera, S., Morang, M.Z., Widener, M.J.: Temporal variability in transit-based accessibility to supermarkets. Appl. Geogr. 53, 149–159 (2014)Google Scholar
  16. 16.
    Coehlo, J.D., Wilson, A.G.: The optimum location and size of shopping centres. Reg. Stud. 10, 413–421 (1976)CrossRefGoogle Scholar
  17. 17.
    Widener, M.J., Farber, S., Neutens, T., Horner, M.: Spatiotemporal accessibility to supermarkets using public transit: an interaction potential approach in Cincinnati. Ohio. J. Transp. Geogr. 42(2015), 72–83 (2015)CrossRefGoogle Scholar
  18. 18.
    Savrasovs, M., Pticina, I.: Methodology of OD matrix estimation based on video recordings and traffic counts. Procedia Eng. 178, 289–297 (2017)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mihails Savrasovs
    • 1
    Email author
  • Irina Pticina
    • 1
  • Valery Zemlynikin
    • 1
  1. 1.Transport and Telecommunication InstituteRigaLatvia

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